Incorrect enzymatic transformation of DNA, may lead to DNA damage, somatic mutation, cancer, genetic disease, aging, and death. Numerous nucleases involved in DNA repair, restriction, and recombination ("RRR") have been widely used to carry out genetic manipulations in vivo and in vitro, to perform medical diagnostics, and as model systems to study enzymatic reactions. This large class of enzymes is therefore of central importance in medicine and biotechnology. Several RRR nucleases were found to exhibit different 3D folds, typically of the alpha-beta class. Our understanding of sequence-structure-function relationships in these enzymes is severely limited by the slow progress of the structure determination - for most of them the 3D structure remains unknown. This project has two goals: 1) to develop a computational method that generates an experimentally validated model of the protein 3D structure, and 2) to apply this method to determine protein folds of RRR nucleases. For members of all RRR nuclease families, large ensembles of models will be generated using protein fold-recognition methods and the de novo structure prediction algorithm ROSETTA. At least 10 candidates for different 3D folds will be selected and probed by cross-linking, chemical modification and mutagenesis. Best models will be identified based on their fit with the experimental data and further tested by additional experiments. The results will advance our understanding of the structural diversity of RRR nucleases and will provide a structural platform for further studies of the processes of DNA repair, restriction, and recombination. Likely candidates for novel folds will be identified, which could be targeted for structure determination by X-ray crystallography. The computer software and the research protocol developed during this study will yield a predictive method for protein structure modeling that will be broadly applicable to all proteins.